Building relationships with consumers has always been a challenging task for a retailer and vice-versa. With the rapid development of diverse e-business solutions, companies are now looking for new opportunities to get in touch with the consumers. Fashion e-commerce brings a lot of functional and financial benefits and makes it very simple and convenient for the consumers with ease of shopping at home.
Besides consumers, the retailers have benefits to expand their clientele worldwide through e-commerce. This helps to increase their business with relatively less efforts related to advertising, sponsorship etc. as the internet has a wide reach around the world. Advantageously, fashion e-commerce acts a boon for consumers as well as retailers when it comes to shop with choice, ease, convenience and earning profit.
Existing fashion e-commerce websites use a variety of filtering techniques to narrow down or refine the search results of a particular product category listing, for example, by size, colour, price or brand. Multiple filters may be applied to take a broad range of products and refine them into a narrower selection, allowing the consumers to retrieve the most relevant search results based on the criteria they have selected. Fashion e-commerce, especially apparel industry still suffers from poor filtering performance because of insufficient filters at granular level.
Currently, most of the fashion e-commerce websites provide generic attribute search such as brand, price, colour and size. However, it can be useful to have finer filtering options which provide unique filters specific to each product type. Such filters enable users to narrow down a website's selection of thousands of products to only those few items that match their particular needs and interests. Moreover, the finer details of the products such as in apparels, may be helpful in identifying design elements that make up the top selling products. Yet, despite it being a central aspect of the user's e-commerce product browsing, most e-commerce websites offer a lacklustre filtering experience.
Hence, there is a need to effectively extract design elements from fashion products to provide filtering at a granular level to help the consumer achieve maximum product discoverability, and reduce any sort of navigation friction. In addition, identified and extracted design elements of a product through finer filters can be used in design automation for in-house branding. Thus, can facilitate a fully-automated design collection, without any human intervention.